eyecandy app dev for audd's music recognition api
-
Updated
Jan 21, 2020 - Swift
eyecandy app dev for audd's music recognition api
I built this to apply machine learning classification techniques to a novel dataset of music I had built up in midi format. It is built in Java.
Front end for music recognition over Linux
⌨️ cli-only version, open-source Shazam client for Linux
Creation of an application to extract the partition of a music. (As Shazam does to recognize music)
TrackRadar is a music recognition bot that uses the Twitter API to identify songs from video content. Enhance your music discovery experience on Twitter with TrackRadar.
Discord Music Recognition Bot
An in-app Music Recognition and Discovery application for Instagram reels, Youtube shorts.
🎵 CLI music recognition using the AudD API
A Twitter bot account that will find the song/music in a video for you.
Learning lab about Optical Music Recognition (OMR) and Music Generation
🎧 Shazam API npm library and CLI tool for music recognition.
A Desktop application for music recognition using audio fingerprinting
During the project for the DIGITAL SIGNAL IMAGE MANAGEMENT course I learned how to manage and process audio and image files. The aim of the project was the classification, through machine learning and deep learning models, of musical genres by extracting specific audio features from the "gtzan dataset" dataset files with which to train the model…
AudD Music Recognition Twitch extension
🔎 🎶 ✔️ Recognizes musical notes on a musical sheet (camera)
Add a description, image, and links to the music-recognition topic page so that developers can more easily learn about it.
To associate your repository with the music-recognition topic, visit your repo's landing page and select "manage topics."